# mirror

Configures Goldsky Mirror pipelines to stream subgraph entities and onchain datasets into databases. Useful when replicating blockchain data to PostgreSQL, ClickHouse, or Kafka.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 3500 installs · ★ 12
- Author: goldsky-io
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/goldsky-io/goldsky-agent/tree/HEAD/skills/mirror/SKILL.md
- Updated: 2026-10-22
- HTML: https://affpapa.org/en/nevibecode/skills/mirror

## What it does

This skill teaches the coding agent how to build and operate Goldsky Mirror streaming pipelines. Mirror reads onchain data from subgraph entities or direct-indexing datasets across 130+ chains. It can run SQL transforms or HTTP handlers before routing records to your sink. Mirror is the only Goldsky pipeline product that supports subgraph sources.

Every pipeline lives in a YAML configuration with `apiVersion: 3`. You deploy it using `goldsky pipeline apply`. For dataset sources, defining a SQL filter alongside `start_at: earliest` triggers Fast Scan for backfills. Supported destinations include PostgreSQL and Kafka.

External destinations require credentials stored as a Goldsky Secret. The deployment fails if `secret_name` is missing. Create this secret beforehand via `goldsky secret create`. When your architecture does not rely on subgraphs, the documentation recommends Turbo pipelines instead.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add goldsky-io/goldsky-agent --skill mirror -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/mirror/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/mirror/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add goldsky-io/goldsky-agent --skill mirror -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/mirror/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add goldsky-io/goldsky-agent --skill mirror -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/mirror/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install goldsky-io/goldsky-agent mirror
```

2. **Manually: put the files in place**
- File: `.github/skills/mirror/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add goldsky-io/goldsky-agent --skill mirror -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/goldsky-io/goldsky-agent --path skills/mirror
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/mirror/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add goldsky-io/goldsky-agent --skill mirror -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/goldsky-io/goldsky-agent/tree/HEAD/skills/mirror/SKILL.md

## When to use it
- stream subgraph entities directly into PostgreSQL or ClickHouse
- generate Mirror pipeline YAML configurations with apiVersion: 3
- speed up historical backfills using Fast Scan filters
- pipe onchain logs and blocks into Kafka topics or AWS SQS queues

## Example prompts
- Generate a Mirror pipeline YAML to stream the account entity from my subgraph to ClickHouse.
- Help me configure a Fast Scan filter for the base.logs dataset with start_at: earliest.
- How do I stream subgraph data into a Kafka topic using goldsky pipeline apply?

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: b7c5e7e570d7c65d.

BEGIN THIRD-PARTY FILE b7c5e7e570d7c65d
````text
---
name: mirror
description: "Use this skill when the user asks about Goldsky Mirror pipelines — creating, deploying, operating, or troubleshooting Mirror. Triggers on: 'Mirror pipeline', 'goldsky pipeline apply', 'sync subgraph to database', 'mirror vs turbo', 'direct indexing', 'mirror pipeline YAML', 'mirror pipeline pause/stop/restart'. Also use this skill when the user wants to sync a Goldsky subgraph into a database or message queue — Mirror is the only pipeline product that supports subgraph sources. For new pipelines that don't need a subgraph source, the turbo-builder skill is usually a better fit. Do NOT trigger on 'goldsky turbo' commands or generic 'build a pipeline' requests without subgraph context — those belong to the turbo skills."
---

# Goldsky Mirror Pipelines

Mirror is Goldsky's original streaming pipeline product. It reads onchain data from a **source** (a subgraph entity or a direct-indexing dataset), optionally applies **transforms**, and writes the result to a **sink** (your database or message queue).

### Mirror vs Turbo — which should you use?

| | Mirror | Turbo |
|---|---|---|
| Subgraph sources | **Yes** | No |
| Speed & reliability | Good | **Faster, more reliable** |
| Sink options | See [common Mirror sinks](#sinks) below | See the [Turbo sink catalog](https://docs.goldsky.com/turbo-pipelines/sinks/overview) |
| Config complexity | Moderate | **Simpler YAML** |
| Dataset coverage | 130+ chains | 130+ chains, richer catalog |

**Use Turbo unless you need a subgraph source.** Turbo is faster, more reliable, and actively gaining feature parity with Mirror — especially sink support. If you don't have a subgraph requirement, say "help me build a Turbo pipeline" and the `/turbo-builder` skill will guide you through a faster setup.

---

## How Mirror Pipelines Work

```
Source (subgraph entity or direct-indexing dataset)
  ↓
Transforms (optional SQL or external handlers)
  ↓
Sink (PostgreSQL, ClickHouse, Kafka, S3, etc.)
```

A pipeline is defined in a YAML file (`apiVersion: 3`) and deployed with `goldsky pipeline apply`.

---

## Pipeline YAML Structure

Top-level fields:

| Field | Type | Required | Description |
| ----- | ---- | -------- | ----------- |
| `name` | string | yes | Lowercase letters, numbers, hyphens only. Under 50 characters. |
| `apiVersion` | number | yes | Always `3` |
| `resource_size` | string | no | `s` (default), `m`, `l`, `xl`, `xxl` |
| `description` | string | no | Pipeline description |
| `sources` | object | yes | At least one source |
| `transforms` | object | no | Use `{}` if none needed |
| `sinks` | object | yes | At least one sink |

---

## Sources

| Source type | YAML `type` value | Description |
| ----------- | ----------------- | ----------- |
| **Subgraph entity** | `subgraph_entity` | Mirror data from Goldsky-hosted subgraphs |
````
END THIRD-PARTY FILE b7c5e7e570d7c65d

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